One of the maxims of being a leader is to make yourself replaceable. I can’t remember what business guru said it, likely because they lost their job before becoming famous.
Like a lot of people, working to make myself replaceable is not an easy concept for me. I have spent the majority of my life trying to make myself irreplaceable as an analyst/decision maker since spending all of 2nd grade analysing the optimal All Star Baseball spin card lineup (hint: leading off George Sisler was the key).
As much as I don’t want to admit it, however, the age of the irreplaceable analyst no longer exists, if it ever did. From my vantage point as GM of the Houston Rockets and the co-chair of the MIT Sloan Sports Analytics Conference, I see a world teeming with really good analysts. Fresh analytical faces are minted each year and sports teams are hiring them in larger numbers. If talented analysts are becoming plentiful, however, then it follows that analysts cannot be the key to creating a consistent winner, as a sustainable competitive edge requires that you have something valuable AND irreplaceable. If better analysts won’t create an edge, however, what will?
The answer is better data. Yep, that’s right. Raw numbers, not the people and programs that attempt to make sense of them. Many organisations have spent the last few years hiring top analysts based on the belief that they create differentiation. Smart companies such as Google believe they need savants to crunch those numbers and find the connections that regular humans could not. But my experience, and what I’m hearing from more organisations (sports and non), shows that real advantage comes from unique data that no one else has.
Here’s an example from my world. Many teams in the NBA track data for their own team such as how often a player on defence challenges shots. When tracked for your own team, this information can be useful to add accountability to the important things a coach is trying to emphasise to win games and to improve players on the margin by increasing their effort on challenging shots. The data does not offer significant competitive leverage, however, until you track the data for the entire league. Only with the league-wide data can you tell if your players are creating an advantage relative to others in the league on shot challenges (higher leverage) or even more important, identify players you may want to acquire who challenge shots extremely well (highest leverage).
Without the context of the entire league, it is very hard to use data in any meaningfully competitive way. Tracking data for the whole league across multiple dimensions is a significant task but very worth it. For obvious reasons, I cannot reveal what data the Houston Rockets track but to track the significant data we gather we use a very large set of temporary labour that helps us develop these data sets that we hope will create an advantage over time. To be sure, you need strong analysts (and we have many) to then work with this data, but the leverage comes not from the analysis but from having the data that others do not.
With the Moneyball movie set to open next month, the world will once again be gaga over the power of smart analytics to drive success. While you are watching the movie, however, think about the fact that the high revenue teams, such as the Red Sox, went out and hired smart analysts and quickly eroded any advantage the Oakland A’s had. If there had been a proprietary data set that Oakland could have built to better value players than the competition, their edge may have been sustainable.
One non-sports company that has known the importance of data to create an advantage for some time and has continued to outpace growth estimates every year because of it is Amazon. Their ability to use unique customer purchase data to drive customised product sales and pricing decisions across a product line with unprecedented breadth has been its key edge over time vs the intense competition from numerous retailers and e-retailers.
While I may not have convinced everyone that data is the key edge (especially the analysts reading this), people in the workforce everywhere should think about what key data you could gather that no one has or even what new product or service you could start that would give you access to data that no one has. That’s the way to create an edge today.